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767 results on '"Cui, Zhihua"'

153. Editorial

Author

Alavi, Amir H., Cui, Zhihua, Gandomi, Amir H., Gao, Xiao-Zhi, Wang, Gai-Ge, and Lim, Meng-Hiot

Published
2018
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154. Knockdown of Long Noncoding RNA 00152 (LINC00152) Inhibits Human Retinoblastoma Progression [Retraction]

Author

Li,Songhe, Wen,Dacheng, Che,Songtian, Cui,Zhihua, Sun,Yabin, Ren,Hua, Hao,Jilong, Li,Songhe, Wen,Dacheng, Che,Songtian, Cui,Zhihua, Sun,Yabin, Ren,Hua, and Hao,Jilong

Abstract

Li S, Wen D, Che S, et al. Onco Targets Ther. 2018;11:3215–3223. The Editor and Publisher of OncoTargets and Therapy wish to retract the published paper. Concerns were raised regarding the alleged manipulation and duplication of tumor images shown in Figure 6B. Specifically: Figure 6B, top row images for sh-NC, appear to be duplicated with images of the same tumors in Figure 2D from Liu et al, 2019 (https://doi.org/10.1016/j.biopha.2019.108862) and Figure 6B from Li et al, 2018 (https://doi.org/10.1016/j.biopha.2018.03.122). Similarly, Figure 6B, bottom row images for sh-LINC00152, also appear to be duplicated with images of the same tumors in Figure 2D from Liu et al, 2019 (https://doi.org/10.1016/j.biopha.2019.108862) and Figure 6B from Li et al, 2018 (https://doi.org/10.1016/j.biopha.2018.03.122). The authors responded to our queries but could not provide a satisfactory explanation for the alleged duplication or provide adequate raw data for their study. The findings of the study were deemed invalid and the Editor requested for the article to be retracted. Our decision-making was informed by our policy on publishing ethics and integrity and the COPE guidelines on retraction. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”. This retraction relates to this paper

Published
2022

164. The global evaluation strategy for many‐objective partial collaborative computation offloading problem.

Author

Xue, Zhaoyu, Guo, Wanwan, Cui, Zhihua, and Zhang, Wensheng

Subjects
BENCHMARK problems (Computer science), INTERNET of things, ENERGY consumption, EVOLUTIONARY algorithms, PROBLEM solving, EDGE computing
Abstract

Summary: With the number of services expanding in the Internet of Things (IoT), the limited resources of user terminals are insufficient to satisfy the computation needs of all running services. Therefore, we design a collaborative computation‐offloading model (CCOM) composed of multiple servers and task offloading modes to solve the problem by offloading tasks from resource‐constrained terminals to other computing entities, which achieves the following four objectives: model execution time minimization, task execution time minimization, energy consumption minimization, and most efficient device workload. And the global evaluation strategy based on angle and distance is proposed to address the individual selection problems caused by the overly localized Pareto dominance relationship and objective conflicts in the many‐objective evolutionary algorithms. In simulations, the strategy achieves the best Inverted Generation Distance (IGD) performance on 22 benchmark test problems based on Wilcoxon's rank sum statistical test and improves performance in the four objectives above by 18%, 31%, 20%, and 42%, respectively. Finally, we think that the strategy can provide adequate offloading performance for decision‐makers. [ABSTRACT FROM AUTHOR]

Published
2023
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179. Preface

Author

Yang, Xin-She, primary, Cui, Zhihua, additional, Xiao, Renbin, additional, Gandomi, Amir Hossein, additional, and Karamanoglu, Mehmet, additional

Published
2013
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